Soluble CD46 as a diagnostic marker of hepatic steatosis

Summary Background The increasing prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) incurs substantial morbidity, mortality and healthcare costs. Detection and clinical intervention at early stages of disease improves prognosis; however, we are currently limited by a lack of reliable diagnostic tests for population screening and monitoring responses to therapy. To address this unmet need, we investigated human invariant Natural Killer T cell (iNKT) activation by fat-loaded hepatocytes, leading to the discovery that circulating soluble CD46 (sCD46) levels accurately predict hepatic steatosis. Methods sCD46 in plasma was measured using a newly developed immuno-competition assay in two independent cohorts: Prospective living liver donors (n = 156; male = 66, female = 90) and patients with liver tumours (n = 91; male = 58, female = 33). sCD46 levels were statistically evaluated as a predictor of hepatic steatosis. Findings Interleukin-4-secreting (IL-4+) iNKT cells were over-represented amongst intrahepatic lymphocytes isolated from resected human liver samples. IL-4+ iNKT cells preferentially developed in cocultures with a fat-loaded, hepatocyte-like cell line, HepaRG. This was attributed to induction of matrix metalloproteases (MMP) in fat-loaded HepaRG cells and primary human liver organoids, which led to indiscriminate cleavage of immune receptors. Loss of cell-surface CD46 resulted in unrepressed differentiation of IL-4+ iNKT cells. sCD46 levels were elevated in patients with hepatic steatosis. Discriminatory cut-off values for plasma sCD46 were found that accurately classified patients according to histological steatosis grade. Interpretation sCD46 is a reliable clinical marker of hepatic steatosis, which can be conveniently and non-invasively measured in serum and plasma samples, raising the possibility of using sCD46 levels as a diagnostic method for detecting or grading hepatic steatosis. Funding F.B. was supported by the Else Kröner Foundation (Award 2016_kolleg.14). G.G. was supported by the Bristol Myers Squibb Foundation for Immuno-Oncology (Award FA-19-009). N.S. was supported by a 10.13039/100010269Wellcome Trust Fellowship (211113/A/18/Z). J.A.H. received funding from the 10.13039/501100007601European Union’s Horizon 2020 research and innovation programme (Award 860003). J.M.W. received funding from the Else Kröner Foundation (Award 2015_A10).


Figure S2. Characteristics of liver resection patients.
Clinical, biochemical and haematological characteristics of study patients according to histological steatosis grade.Groups were compared using Fisher's Exact Test or Kruskal-Wallis Test.p-values were not adjusted for multiple comparisons.

Figure S4 .
Figure S4.Phenotyping of human iNKT cells after coculture with HepaRG cells.(A) Optimized flow cytometry panel for assessing human iNKT cell differentiation following in vitro expansion.(B) Flow cytometry gating strategy to determine the frequency of cytokine-expressing CD4 + iNKT cells.(C) Frequency of IFN-γ + iNKT cells after a 7-day expansion in the presence of fat-loaded (FL)-or unloaded (UL)-HepaRG cells [n=8; Wilcoxon matched-pairs signed rank test].(D) Frequency of IL-17A + iNKT cells after a 7-day expansion in the presence of fat-loaded (FL)-or unloaded (UL)-HepaRG cells [n=8; Wilcoxon matched-pairs signed rank test].(E) Frequency of IL-22 + iNKT cells after a 7-day expansion in the presence of fat-loaded (FL)-or unloaded (UL)-HepaRG cells [n=8; Wilcoxon matched-pairs signed rank test].(F) Frequency of IL-4 + iNKT cells after a 7-day expansion in indirect cocultures with fat-loaded (FL)-or unloaded (UL)-HepaRG cells [n=8;Wilcoxon matched-pairs signed rank test].(G) Consistent with HepaRG cells specifically suppressing IL-4 + iNKT cells, no effect was observed of FL-or UL-HepaRG cells on IL-4 production by conventional T cells [n=7; Friedman test with Dunn's multiple comparisons test].

Figure S5 .
Figure S5.Technical controls for shRNA-silencing of CD46 in HepaRG cells.(A) Flow cytometry panel for quantifying cell-surface expression of CD46 in HepaRG cells.(B) Representative flow cytometry results showing down-regulation of cellsurface CD46 expression in HepaRG cells transfected with CD46-shRNA, but not a random shRNA control.(C) Mean Fluorescence Intensity (MFI) of CD46 expression on unloaded HepaRG cells that were stably transfected with either random shRNA or CD46-knockdown shRNA.Untransfected HepaRG cells are taken as controls.[n=3 independent experiments; Friedman test with Dunn's test for multiple comparisons].(D) Western blot of CD46 expression showing down-regulation in HepaRG cells transfected with CD46-shRNA, but not a random shRNA control.

Figure S6 .
Figure S6.Cell-based Assay to Quantify sCD46 (Standard Operating Procedure) a Diagnostic Marker of Hepatic Steatosis -Bitterer F. et al.

based Assay to Quantify sCD46
Soluble CD46 as a Diagnostic Marker of Hepatic Steatosis -Bitterer F. et al.

Performance metrics for sCD46 and Fatty Liver Index in predicting steatosis
Soluble CD46 as a Diagnostic Marker of Hepatic Steatosis -Bitterer F. et al.Soluble CD46 as a Diagnostic Marker of Hepatic Steatosis -Bitterer F. et al.Soluble CD46 as a Diagnostic Marker of Hepatic Steatosis -Bitterer F. et al.Soluble CD46 as a Diagnostic Marker of Hepatic Steatosis -Bitterer F. et al.Performance metrics for sCD46 as a predictor of grade 0-1 steatosis versus grade 2-3 steatosis assessed by histology in the Validation Set with a threshold = 45.55 ng/ml Soluble CD46 as a Diagnostic Marker of Hepatic Steatosis -Bitterer F. et al.
(A) Performance metrics for sCD46 as a predictor of no steatosis versus steatosis assessed by ultrasonography.(B) Performance metrics for Fatty Liver Index as a predictor of no steatosis versus steatosis assessed by ultrasonography.a b